CorrespondencePublished: 09 October 2026Daniel S. Terry ORCID: orcid.org/0000-0001-9021-00841,Roman Kiselev ORCID: orcid.org/0000-0003-3290-62211,Manuel F. Juette ORCID: orcid.org/0000-0002-8760-80802,Zeliha Kilic ORCID: orcid.org/0000-0002-3287-95611,Ryan A. Brady ORCID: orcid.org/0000-0002-0408-32241,Yuansheng Sun ORCID: orcid.org/0000-0001-6893-97761 &…Scott C. Blanchard ORCID: orcid.org/0000-0003-2717-93651 Nature Methods (2026) Cite this articleSave articleView saved researchSingle-molecule fluorescence resonance energy transfer (smFRET) has become a core technique for structural biology because it can observe the dynamics of biological systems in real time1. Total internal reflection fluorescence (TIRF) microscopy of surface-tethered particles with scientific complementary metal oxide semiconductor (sCMOS) cameras enables smFRET imaging of more than 10,000 particles simultaneously2. A central challenge in the adoption of this technique has been the availability of robust software for this specialized imaging modality. Here, we present an integrated, open-source toolkit that provides an end-to-end solution for single-molecule imaging, from co-ordination and execution of instrument control through to quantitative analysis.FLASH supports commonly used devices for TIRF–smFRET, including cameras, lasers, data acquisition synchronization devices, acousto-optic tunable filters, optomechanics, power meters, microscope stands and motorized sample stages. The software architecture (Supplementary Note 1) follows the ‘actor’ paradigm, with commands packaged as one-way messages to communicate asynchronously between actor modules that represent each user interface, hardware device and data processing service. This approach minimizes coupling between modules, facilitates parallelization and improves fault tolerance. The user interface (Fig. 1a and Supplementary Fig. 1) includes quality-of-life features such as a schematic of the microfluidic device with current stage position and travel limits, live particle counter, and automatic selection of optimal imaging parameters to achieve a desired time resolution. FLASH also enables automation of common workflows, including arraying parameters such as stage position, laser power and exposure time (Supplementary Fig. 2a) while ensuring optimal focus across each movie in a series with image-based autofocus (Supplementary Fig. 2b,c). FLASH currently supports devices from a basis set of popular vendors, and we anticipate that its modular architecture, extensive documentation and open-source release will encourage other laboratories to contribute modules for their devices.This is a preview of subscription content, access via your institutionAccess options Access through your institutionAccess Nature and 54 other Nature Portfolio journalsGet Nature+, our best-value online-access subscription27,99 € / 30 dayscancel any timeLearn moreSubscribe to this journalReceive 12 print issues and online access269,00 € per yearonly 22,42 € per issueLearn moreBuy this articlePurchase on SpringerLinkInstant access to the full article PDF.39,95 €Prices may be subject to local taxes which are calculated during checkoutFig. 1: Tools for instrument control, hardware triggering and data analysis.SubjectsData acquisitionSingle-molecule biophysicsSoftwareTotal internal reflection microscopyCode availabilityAll software, documentation, and CAD drawings for 3D printing are freely available at https://github.com/stjude-smc/.ReferencesLerner, E. et al. 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Methods 15, 669–676 (2018).Article CAS PubMed PubMed Central Google Scholar Lerner, E. et al. eLife 10, e60416 https://doi.org/10.7554/eLife.60416 (2021).Article CAS PubMed PubMed Central Google Scholar Download referencesAcknowledgementsWe thank the Single-Molecule Imaging Center at St. Jude for instrumentation and staff support. We also thank the laboratories of J. Munro, W. Mothes, M. Lu and D. K. Das for testing early versions of FLASH. Finally, we thank the many users of SPARTAN from around the world who have provided feedback, reported bugs, or suggested features.FundingThis work was supported by the US National Institutes of Health (grants R01GM098859, R01GM079238, RM1HG011563 and R35GM163846 to S.C.B.). This work was also supported by the St. Jude Children’s Research Hospital Collaborative Research Consortium on G-Protein Coupled Receptors (GPCRs).Author informationAuthors and AffiliationsSt. Jude Children’s Research Hospital, Memphis, TN, USADaniel S. Terry, Roman Kiselev, Zeliha Kilic, Ryan A. Brady, Yuansheng Sun & Scott C. BlanchardWeill-Cornell Medicine, New York, NY, USAManuel F. JuetteAuthorsDaniel S. TerryView author publicationsSearch author on:PubMed Google ScholarRoman KiselevView author publicationsSearch author on:PubMed Google ScholarManuel F. JuetteView author publicationsSearch author on:PubMed Google ScholarZeliha KilicView author publicationsSearch author on:PubMed Google ScholarRyan A. BradyView author publicationsSearch author on:PubMed Google ScholarYuansheng SunView author publicationsSearch author on:PubMed Google ScholarScott C. BlanchardView author publicationsSearch author on:PubMed Google ScholarContributionsD.S.T., with contributions from M.F.J., Z.K. and R.K., developed SPARTAN. D.S.T. and M.F.J., with contributions from R.K. and Y.S., developed FLASH. R.K. developed Microsync. R.A.B. performed TIRF imaging experiments demonstrating automated data collection. All authors contributed to writing the manuscript. S.C.B. supervised the project.Corresponding authorCorrespondence to Scott C. Blanchard.Ethics declarationsCompeting interestsS.C.B. has an equity interest in Lumidyne Technologies. The remaining authors declare no competing interests.Peer reviewPeer review informationNature Methods thanks the anonymous reviewers for their contribution to the peer review of this work.Supplementary informationRights and permissionsReprints and permissionsAbout this article